# data for censored fitting problem.
srand(10);

n = 20;  # dimension of x's
M = 25;  # number of non-censored data points
K = 100; # total number of points
c_true = randn(n,1);
X = randn(n,K);
y = X'*c_true + 0.1*(sqrt(n))*randn(K,1);

# Reorder measurements, then censor
sort_ind = sortperm(vec(y));
y = sort(vec(y));
X = X[:,sort_ind];
D = (y[M]+y[M+1])/2;
y = y[1:M];
